Dmitriy Gizlyk
Codes
Tick Chart for MetaTrader 4
The presented indicator plots a fully-functional tick chart similar to the standard price charts, with the ability of the analysis using all the MetaTrader features
Articles
Neural networks made easy (Part 13): Batch Normalization for MetaTrader 5
In the previous article, we started considering methods aimed at improving neural network training quality. In this article, we will continue this topic and will consider another approach — batch data normalization
Neural networks made easy (Part 12): Dropout for MetaTrader 5
As the next step in studying neural networks, I suggest considering the methods of increasing convergence during neural network training. There are several such methods. In this article we will consider one of them entitled Dropout
Neural networks made easy (Part 11): A take on GPT for MetaTrader 5
Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in
Neural networks made easy (Part 10): Multi-Head Attention for MetaTrader 5
We have previously considered the mechanism of self-attention in neural networks. In practice, modern neural network architectures use several parallel self-attention threads to find various dependencies between the elements of a sequence. Let us consider the implementation of such an approach and
Neural networks made easy (Part 9): Documenting the work for MetaTrader 5
We have already passed a long way and the code in our library is becoming bigger and bigger. This makes it difficult to keep track of all connections and dependencies. Therefore, I suggest creating documentation for the earlier created code and to keep it updating with each new step. Properly
Neural networks made easy (Part 8): Attention mechanisms for MetaTrader 5
In previous articles, we have already tested various options for organizing neural networks. We also considered convolutional networks borrowed from image processing algorithms. In this article, I suggest considering Attention Mechanisms, the appearance of which gave impetus to the development of
Neural networks made easy (Part 7): Adaptive optimization methods for MetaTrader 5
In previous articles, we used stochastic gradient descent to train a neural network using the same learning rate for all neurons within the network. In this article, I propose to look towards adaptive learning methods which enable changing of the learning rate for each neuron. We will also consider
Neural networks made easy (Part 6): Experimenting with the neural network learning rate for MetaTrader 5
We have previously considered various types of neural networks along with their implementations. In all cases, the neural networks were trained using the gradient decent method, for which we need to choose a learning rate. In this article, I want to show the importance of a correctly selected rate
Neural networks made easy (Part 5): Multithreaded calculations in OpenCL for MetaTrader 5
We have earlier discussed some types of neural network implementations. In the considered networks, the same operations are repeated for each neuron. A logical further step is to utilize multithreaded computing capabilities provided by modern technology in an effort to speed up the neural network
Neural networks made easy (Part 4): Recurrent networks for MetaTrader 5
We continue studying the world of neural networks. In this article, we will consider another type of neural networks, recurrent networks. This type is proposed for use with time series, which are represented in the MetaTrader 5 trading platform by price charts